fMRI scans help reveal ‘fingerprints’ of mental diseases

A team of U.S. researchers found the brains of patients diagnosed with severe mental illnesses—such as schizophrenia and depression—may have more in common than previously thought, according to an fMRI study published in in Proceedings of the National Academy of Sciences of the United States of America.

Utilizing a concept called connectomics—which measures all connections in the brain at once—the team found psychiatric conditions are not subject to neurological boundaries, but share underlying causes across distinct pathologies, wrote lead researcher Justin T. Baker, MD, PhD, scientific director of the McLean Institute for Technology in Psychiatry, Belmont, Massachusetts.

“For most studies, illnesses are studied in isolation, but evidence strongly suggests that distinct psychiatric diagnoses are not separated by clear neurobiological boundaries," Baker added in a prepared statement. "The approach we've taken is to look at the whole brain so you can see not only how individual systems—like the visual system and motor system—are functioning, but how higher order systems—like cognitive systems—are functioning in the brain to see if there are correlations."

Baker and colleagues from Yale University studied fMRI scans of 1,010 patients collected between November 2008 and June 2017. Of that total, 210 were diagnosed with a primary psychotic disorder (schizophrenia or bipolar disorder with psychosis), 192 presented with a primary affective disorder without psychosis (26 with bipolar disorder without psychosis, 57 treatment-seeking individuals with unipolar depression, 109 nontreatment-seeking individuals with unipolar depression) and 608 data-quality-matched healthy participants.

The researchers found “striking evidence” indicating disease connectomic “fingerprints” that are commonly disrupted across specific pathologies. Findings also suggested these fingerprints scale along with clinical severity.

Affective and psychotic illness was associated with disruptions in frontoparietal network connectivity. Additionally, aspects of default network connectivity were disrupted in patients with psychotic illness, but not those with psychotic symptoms, the authors noted.

"The study begins to give us a better way of seeing how schizophrenia, bipolar disorder, and depression are similar or have shared underlying causes," Baker said. “ There is significant genetic risk for schizophrenia and bipolar disorder, and we also know that these conditions affect certain parts of the brain, but this study highlights that one system is affected or disrupted as a function of how severe the illness is, irrespective of whether it was psychosis or an affected illness like depression."

There are limitations that readers need to consider, the authors acknowledged. Conclusions are limited to patients who did not seek treatment, for example, as opposed to those from inpatient hospitalization programs.

Going forward, the team will continue to apply their research to further the understanding of mental diseases.

“We want to see if there is a fingerprint for different conditions and then use that information and apply it to the individual," Baker said. "We are conducting studies that follow individuals over time to look at the brain to see how symptoms are changing. We're trying to go from the snapshot view of these biomarkers to something that is much more dynamic and captures changes and nuances."